A technique for optimally assigning nursing personnel to patient care responsibilities will be developed, tested, implemented, and evaluated. The technique will be based on a methodology already developed for obtaining a measure of the difficulty of nursing assignment which reflects the task groups and condition of patients included in the assignment. In this research project, questions regarding the capacity for difficulty will be investigated, especially as capacity relates to the proportion of time spent in activities and an index of the quality of nursing care. Work-sampling and task completion indices will be used in this portion of the research. A nursing personnel assignment algorithm will be developed which will be useful at all levels of personnel assignment decision making within the nursing organization. The model will consider all personnel types available for assignment during any work period for whom difficulty data have been obtained. It will have the capability of balancing work assignments between personnel on the same patient unit and between units in the same hospital. It will permit head nurses to judge the maximum amount of difficulty to be assigned to any one individual staff member and thus permit quantitatively managed individual responsibilities. The model will optimize assignments on the basis of overall expected quality of care (task completion), expected time spent in provision of patient care, and assignment balance. It will determine the benefits to be derived from the addition of personnel and the costs incurred. It will be used to investigate the effects of various patterns of assignment and staff mix policies on the difficulty of assignments determined. Solutions of the model for specific situations will be compared to assignments made by head nurses and team leaders as one measure of the model's effectiveness. Regimens for using the algorithm in simplified form without the aid of an on-line computer will be developed. Personnel acceptance of the technique after implementation and its cost effectiveness from the standpoint of personnel savings or increased patient care will be determined.